Why We Are Losing the War Against COVID-19 on the Data Front and How to Reverse the Situation.

With over 117 million COVID-19-positive cases declared and the death count approaching 3 million, we would expect that the highly digitalized health systems of high-income countries would have collected, processed, and analyzed large quantities of clinical data from patients with COVID-19. Those data should have served to answer important clinical questions such as: what are the risk factors for becoming infected? What are good clinical variables to predict prognosis? What kinds of patients are more likely to survive mechanical ventilation? Are there clinical subphenotypes of the disease? All these, and many more, are crucial questions to improve our clinical strategies against the epidemic and save as many lives as possible. One might assume that in the era of big data and machine learning, there would be an army of scientists crunching petabytes of clinical data to answer these questions.

Cuba's Pedro Kourí Tropical Medicine Institute:Battling COVID-19 One Study, One Test, One Patient at a Time.

This MEDICC Review roundtable brings you specialists from Havana's Pedro Kourí Tropical Medicine Institute (IPK), who are working directly with testing, research and patient care during the COVID-19 pandemic. Founded in 1937 by its namesake, the Institute has gained considerable worldwide prestige. Today, it is a PAHO-WHO Collaborating Center for the Study of Dengue and Its Vector, and for the Elimination of Tuberculosis.

"Universal" doesn't just apply to health care, but to every sector's actions taken to protect the population's health.

Dr Pastor Castell-Florit's career in public health spans work at local, na-tional and international levels. In 2016, he received PAHO's Award for Health Administration in the Americas, for "outstanding leadership and valuable contributions to the management and administration of the Cuban National Health System." He serves as presi-dent of Cuba's National Council of Sci-entific Societies in Health, as director of the National School of Public Health, and is a member of the Cuban Acad-emy of Sciences.

[Child development in poor areas of Peru].

Objectives: The objective of the study was to demonstrate the influence of several socioeconomic factors on the motor and language development of children under 5 from the baseline study conducted within the framework of the Joint Program for Children, Food Security, and Nutrition, implemented by five United Nations agencies across 65 districts in the departments of Loreto, Ayacucho, Huancavelica, and Apurímac, Peru.

Methods: Dichotomous logistic regression models were used to estimate the likelihood of achievement of motor and language milestones, while polynomial regression models were used to estimate the last milestone achieved and the number of milestones achieved. The study analyzes the influence that maternal education, urban vs.